Compare construction prices across regions and categories. Returns detailed price statistics, percentiles, and regional rankings. Args: regions: Comma-separated regions to compare (e.g. 'Москва,Санкт-Петербург'). Empty = all. category: Filter by category. Empty = all.
| Name | Required | Description | Default |
|---|---|---|---|
| regions | No | ||
| category | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool returns 'detailed price statistics, percentiles, and regional rankings', which adds behavioral context beyond the schema. However, without annotations, it lacks information on destructive potential, authentication needs, or error handling. The empty input behavior is clarified, but completeness is modest.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with three clear sentences: purpose, return content, and parameter explanations. Front-loaded with the key action and resource, no superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only 2 parameters and an output schema, the description covers inputs (including defaults) and outputs (statistics, percentiles, rankings). It is mostly complete, though it could specify acceptable category values or region format more precisely.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% description coverage, so the description fully carries parameter meaning. It explains 'regions' as comma-separated and notes empty defaults mean all. This adds significant value beyond the schema's bare definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares construction prices across regions and categories, using specific verb 'Compare' and resource 'construction prices'. However, it does not differentiate from sibling tool 'region_comparison', which might have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for price comparison but provides no guidance on when to use this tool versus alternatives like 'calculate_cost' or 'market_analytics'. No when-not or explicit context about prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes: search_companies, find_best_companies, smart_match, and contractor_recommendation all find contractors; get_company, company_portfolio, and company_deep_profile all return company details; calculate_cost and project_estimator both estimate costs. This makes it difficult for an agent to reliably choose the correct tool.
Tool names mix verb-first patterns (get_*, search_*, compare_*, calculate_*, export_*, find_*, request_*) with noun-first patterns (company_deep_profile, market_report, price_comparison, etc.). All names use snake_case, but the inconsistent verb/noun placement makes the set less predictable.
24 tools falls squarely in the 16-25 'feel heavy' range. While the server covers a broad domain (companies, projects, analytics, leads, estimation), the presence of many overlapping tools suggests the count could be consolidated without losing functionality.
The toolset covers the core domain well: searching companies and projects, retrieving full details, comparing entities, estimating costs, obtaining market analytics, and managing the lead lifecycle (request_quote -> get_lead_status). Minor gaps exist (e.g., no detailed per-review text, but that is explicitly stated as unavailable), but there are no dead ends for typical workflows.